Outcomes of a Mobile Phone Intervention for Heart Failure in a Minority County Hospital Population

Introduction

Heart failure (HF) is a complex disease that affects over 5 million people in the United States. ¹ HF is a leading cause of hospital admissions and readmissions, reduced quality of life (QoL), and increased mortality; it poses an increasing burden and cost as the population ages. ^2,3 Some evidence suggests that frequent monitoring can lead to early detection of decompensation, resulting in early intervention and thereby reduction of readmissions. ⁴ The American College of Cardiology/American Heart Association Guidelines for the Management of HF recommend daily weight monitoring as the cornerstone for the management of patients with HF. ⁵ Innovative methods to follow changes in weight and symptoms may improve the poor outcomes in HF patients.

HF patients who are actively involved in their own care and adhere to treatment regimens are more likely to have improved survival and decreased readmission rates and experience better QoL. ^6,7 Previous studies on traditional telemonitoring of HF patients have suggested its potential to reduce hospitalizations, costs, and mortality, as well as to improve QoL and self-care, but the results have been inconsistent. ^{5,8 –11} Mobile phones are ubiquitous, low cost, and scalable ¹² and offer a unique opportunity with automated interactive features for text messaging, data gathering, reminders, and alerts. However, few HF disease management programs have used a mobile phone system. ^13,14

There is still a critical gap in the feasibility and effectiveness of mobile phone-based HF programs overall, specifically in minority populations. Our study was funded as a technology transfer–commercial partnership grant to develop a usable cellular phone-based HF monitoring system and to conduct a randomized controlled trial to assess its effect. The main hypothesis was that daily monitoring using an automated system of mobile phone-based text queries, using simple yes–no responses related to key HF signs and symptoms, would improve patient self-care efficacy, knowledge, and QoL. The usability outcomes and challenges will be discussed in a separate article.

Materials and Methods

We implemented a mobile phone technology system offering automated daily monitoring of weight and symptoms of HF and conducted a proof-of-principle study. The University of Miami IRB approved this study before commencement.

Participants

Seven hundred and eighteen patients receiving care from the Heart Failure Clinic at Jackson Memorial Hospital, a county hospital in Miami, were prescreened and 296 of them met the eligibility criteria. Eligible participants were community-dwelling ambulatory patients diagnosed with HF. Other eligibility criteria included age ≥18 years; ability to speak and read English or Spanish; anticipated survival ≥6 months; no previous history of unstable coronary syndromes; no end-stage HF; and no heart transplantation. Of the 296 eligible patients, 184 were screened in person for their interest in the study, ability and willingness to operate the mobile phone, and read, comprehend, and respond to the mobile phone-based text queries. At the screening visit, 123 patients declined to participate in the study. The most common reasons were not enough compensation, too much time commitment, not motivated, and others just said no. We randomized the remaining 61 patients in a 2:1 ratio to two groups: Mobile phone Intervention (n = 42) and Usual care (n = 19). Figure 1 shows the CONSORT diagram.

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Fig. 1.

CONSORT Diagram.

Results

Baseline overall and group-specific sociodemographic, mobile phone use, anthropometric, and clinical characteristics of the participants are shown in Tables 2 and 3 . Overall, 75% of the participants were Hispanic; 25% were African American.

Outcomes

Table 4 shows the results of the assessments performed at baseline and at 3 months, as well as the corresponding changes.

Discussion

This randomized controlled trial was the first of its kind, to our knowledge, to use a mobile phone Web browser messaging application that monitored daily weights and HF symptoms in a multiethnic, predominantly Hispanic, county hospital population for 3 months. The intervention improved self-efficacy and QoL among intervention participants compared with usual care.

Our mobile intervention improved the patients' chronic disease and HF-specific self-efficacy, their efficacy to communicate with physicians, and their QoL. It also improved health distress relative to the control group, in which health distress worsened. Earlier studies using nonmobile telehealth interventions show similar results. Dorsch et al. showed that a Web application used for symptom monitoring and links to HF goals and educational materials improved symptoms in systolic HF. ²⁶ In two other studies, daily weight monitoring along with education improved knowledge and self-care implementation of daily weight monitoring. ^27,28 However, these previous interventions used a combination of HF monitoring along with an educational component. ^{26 –28}

Self-efficacy refers to the belief in one's ability to respond to challenges and carry out a behavior necessary to reach a desired goal. Increased self-efficacy is related to improved disease outcomes. ^29,30 In fact, previous studies in diabetes and asthma have shown that self-efficacy rather than patient education or knowledge is vital in improving outcomes. ^31,32 Our results are especially encouraging because improvement in self-efficacy occurred without a defined educational component in our mobile phone intervention. This suggests that a parameter-focused approach to symptom monitoring alone may reinforce the importance of daily monitoring and understanding of their condition among patients and promote good disease self-management skills and facilitate behavior change. It is also likely that increase in patient efficacy is not due to the frequent monitoring alone, but rather to the increased interactions with the healthcare system through the study coordinator, who contacted them whenever there was a response suggestive of deterioration of HF, such as weight gain, increased shortness of breath, or swelling in the feet. Our results are encouraging because they suggest that automated communications that trigger appropriate alerts and interactions with care providers in response to status changes may improve self-care efficacy. Seto et al. also evaluated the effects of a mobile phone-based telemonitoring system on self-care and clinical management of HF and showed that it improved QoL through improved self-care. ¹⁴ Our system was less automated compared with Seto's, with no automated feedback loop, except to ask participants to call their study coordinator and HF clinic. However, even our simple intervention of yes–no responses improved self-efficacy.

To the best of our knowledge, this is the first study of its kind to evaluate the use and outcomes of a cellular Web browser messaging program to monitor daily symptoms and engage predominantly Hispanic patients with HF in self-managing their disease. Even though the study was not powered to detect differences in healthcare utilization, by increasing self-efficacy, interventions such as ours may possibly help HF patients avoid costly events such as emergency visits and admissions when implemented in the immediate posthospital discharge period. Lee et al. recently demonstrated that self-efficacy is a key component of HF care in a randomized controlled HF trial wherein intervention patients used a symptom diary with education and counseling sessions compared with usual care. More intervention patients had event-free survival compared with usual care (78.3% active group versus 47.6% usual care; p = 0.03). ³³ Another study reported that HF patients more engaged in self-management had a 56% reduction in mortality and healthcare utilization compared with patients who were less engaged in self-management. ³⁴

Our intervention did not target knowledge. Therefore, it was no surprise that knowledge scores did not improve in the intervention group. However, knowledge scores did improve in the control group. Upon enrollment, all participants in both groups received some basic HF education reminding them to weigh themselves and information on monitoring and reporting positive symptoms, etc. This likely impacted knowledge more positively in the control group than the intervention group because the control group had significantly lower mean knowledge scores at baseline.

There are inherent limitations in the study, in that we cannot exclude sampling bias, the Hawthorne effect, and repeated testing bias that may have occurred during the study. We enrolled minority patients from the Heart Failure Clinic at a large county hospital, who may not be representative of the general population with HF. However, we attempted to negate these effects by the wide range of outcomes measured and by having a control group. In addition, several participants in both groups were seen in the Heart Failure Clinic during the study. Self-management teaching at any of these contacts, or simply improvement in health status, may account for the observed improvements. However, the fact that improvements in outcomes occurred after the intervention implicates a causal link. The cause and effect relationship is also suggested by the fact that the change in the control group was in the negative direction for several outcomes, including SECD, GH, HDS, and FVN. Although the sample size is small, the results are still positive; it is likely that a larger study would reveal more robust outcomes. A limitation of the study is that the intervention was too short to elucidate the benefits of daily monitoring and perhaps a longer intervention would have shown a greater impact. Future studies should validate these preliminary findings in a longer, larger randomized trial offered postdischarge from the hospital and assess their impact on healthcare utilization and cost.

Implementation of a mobile monitoring and reminder system that can increase self-efficacy and identify deterioration preemptively would be immensely beneficial. These promising results underscore the unique scalable opportunity mobile phones present to address the ethnic disparity and digital divide in HF management. More work is necessary to understand the key ingredients of successful intervention programs. The role of technology (for monitoring and/or education) versus case management in such programs and the role each plays in patient education, medication adherence, and preemptive intervention need further elucidation. ³⁵ Besides mobile interventions to improve patient self-efficacy, further research will need to focus on development of sophisticated sensitive and specific algorithms for automated analysis of home monitoring data and to close the feedback and care loop to make mobile monitoring effective and efficient.